Surveillance systems typically consist of a camera and monitor. Sensors are often added to notify a user if a person or object has come within the range of view of the sensor. The problem with such a system however, is that it does not identify the object or recognize the object as having been previously identified. Fingerprinting an object is the ability to identify an object based on unique features of the object. Because objects move through environments in a dynamic fashion and because of changing views and occlusion, fingerprinting objects is inherently a dynamic problem.
While there have been methods for tracking and recognizing objects from static images, there have been none that address the problem of tracking and recognizing in dynamic environments where the objects and the sensors that track and sense them are moving simultaneously. Additionally, there are currently no methods for acquiring fingerprint models of objects in an incremental and automated fashion under dynamically varying environments.
Thus, a continuing need exists for a system that allows for object identification, tracking, and fingerprinting in a dynamic environment.